Kwok Kin O, Cowling Benjamin J, Wei Vivian W I, Wu Kendra M, Read Jonathan M, Lessler Justin, Cummings Derek A, Peiris J S Malik, Riley Steven
School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China.
Faculty of Health and Life Sciences, Department of Epidemiology and Population Health, Institute of Infection and Global Health, University of Liverpool, Liverpool, UK.
Proc Biol Sci. 2014 Aug 22;281(1789):20140709. doi: 10.1098/rspb.2014.0709.
The interaction of human social behaviour and transmission is an intriguing aspect of the life cycle of respiratory viral infections. Although age-specific mixing patterns are often assumed to be the key drivers of the age-specific heterogeneity in transmission, the association between social contacts and biologically confirmed infection has not previously been tested at the individual level. We administered a questionnaire to participants in a longitudinal cohort survey of influenza in which infection was defined by longitudinal paired serology. Using a variety of statistical approaches, we found overwhelming support for the inclusion of individual age in addition to contact variables when explaining odds of infection: the best model not including age explained only 15.7% of the deviance, whereas the best model with age explained 23.6%. However, within age groups, we did observe an association between contacts, locations and infection: median numbers of contacts (or locations) reported by those infected were higher than those from the uninfected group in every age group other than the youngest. Further, we found some support for the retention of location and contact variables in addition to age in our regression models, with excess odds of infection of approximately 10% per additional 10 contacts or one location. These results suggest that, although the relationship between age and incidence of respiratory infection at the level of the individual is not driven by self-reported social contacts, risk within an age group may be.
人类社会行为与传播之间的相互作用是呼吸道病毒感染生命周期中一个引人入胜的方面。尽管年龄特异性混合模式通常被认为是传播中年龄特异性异质性的关键驱动因素，但社会接触与经生物学确认的感染之间的关联此前尚未在个体层面进行过测试。我们对一项流感纵向队列研究的参与者进行了问卷调查，其中感染是通过纵向配对血清学定义的。使用多种统计方法，我们发现，在解释感染几率时，除了接触变量外，纳入个体年龄得到了压倒性的支持：不包括年龄的最佳模型仅解释了15.7%的偏差，而包含年龄的最佳模型解释了23.6%。然而，在各年龄组内，我们确实观察到接触、地点与感染之间存在关联：除最年幼年龄组外，每个年龄组中报告的感染人群的接触（或地点）中位数均高于未感染组。此外，我们发现，在回归模型中，除年龄外保留地点和接触变量也有一定依据，每增加10次接触或一个地点，感染几率会额外增加约10%。这些结果表明，虽然在个体层面上，年龄与呼吸道感染发病率之间的关系并非由自我报告的社会接触驱动，但在一个年龄组内风险可能是由社会接触驱动的。
